Efficacy and Ethics of AI-Delivered Psychological Support for Chronic Illness in Low-Income Settings: A Mixed-Methods Study among Iranian Health Professionals

AI-driven psychological interventions offer scalable solutions for chronic illness patients in resource-limited settings, yet evidence gaps persist in low-income countries regarding efficacy, ethics, and implementation. A mixed-methods study (systematic review, survey of 122 Iranian health professionals, and 18 qualitative interviews) evaluated AI’s role in psychological support. The review analyzed 10 studies (2020–2025), while survey and interview data explored practitioner perceptions. The review identified efficacy in middle-income settings (e.g., chatbots reduced distress in Egyptian breast cancer patients [RCT, n=150]), but no studies in low-income countries. Survey results revealed high optimism for AI’s accessibility (90.2%) but significant concerns about privacy (76.2%) and cultural relevance (61.5%). Qualitative themes highlighted demands for dialect-adapted NLP, human escalation protocols, and integration with community health workers. AI tools show promise for expanding mental health care, but their success hinges on contextual adaptation, ethical safeguards, and infrastructure investment. Policymakers must address digital literacy and regulatory gaps to enable equitable deployment.

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Publication Details

Journal
InfoScience Trends
Published
2025-04-21
DOI
https://doi.org/10.61186/ist.202502.04.06
Citations
1
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
1.54
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article

Efficacy and Ethics of AI-Delivered Psychological Support for Chronic Illness in Low-Income Settings: A Mixed-Methods Study among Iranian Health Professionals

Amir Emami, Naser Ahmadi, Neda Shalbaf, Khatereh Nasirimehr
1 citations
InfoScience Trends
Digital Mental Health Interventions
1.54
article

Efficacy and Ethics of AI-Delivered Psychological Support for Chronic Illness in Low-Income Settings: A Mixed-Methods Study among Iranian Health Professionals

Amir Emami, Naser Ahmadi, Neda Shalbaf, Khatereh Nasirimehr
article en
1 citations

Abstract

AI-driven psychological interventions offer scalable solutions for chronic illness patients in resource-limited settings, yet evidence gaps persist in low-income countries regarding efficacy, ethics, and implementation. A mixed-methods study (systematic review, survey of 122 Iranian health professionals, and 18 qualitative interviews) evaluated AI’s role in psychological support. The review analyzed 10 studies (2020–2025), while survey and interview data explored practitioner perceptions. The review identified efficacy in middle-income settings (e.g., chatbots reduced distress in Egyptian breast cancer patients [RCT, n=150]), but no studies in low-income countries. Survey results revealed high optimism for AI’s accessibility (90.2%) but significant concerns about privacy (76.2%) and cultural relevance (61.5%). Qualitative themes highlighted demands for dialect-adapted NLP, human escalation protocols, and integration with community health workers. AI tools show promise for expanding mental health care, but their success hinges on contextual adaptation, ethical safeguards, and infrastructure investment. Policymakers must address digital literacy and regulatory gaps to enable equitable deployment.

InfoScience TrendsVol. 2(4)
Imam Hossein Hospital (IR), Shahid Beheshti University of Medical Sciences (IR), Babol University of Medical Sciences (IR), Mazandaran University of Medical Sciences (IR)
No poverty
Openalex Percentile: Top 18%
Digital Mental Health Interventions
1.54
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Efficacy and Ethics of AI-Delivered Psychological Support for Chronic Illness in Low-Income Settings: A Mixed-Methods Study among Iranian Health Professionals — Amir Emami, Naser Ahmadi, et al. · InfoScience Trends (2025) | TGRS Research Map | TGRS